Showing 11 results for Type of Study: Letter to Editor
M Bazyar, E Barfar,
Volume 9, Issue 2 (10-2013)
Abstract
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Mh Mehrolhassani, Aa Haghdoost, R Dehnavieh, M Abolhallaje, M Emami,
Volume 12, Issue 0 (3-2017)
Abstract
Governance and leadership are seen as the most important function in the realization and promotion of community health. This two components through legislation must identify present situation, determine the desirable situation, provide infrastructures and implementation mechanisms and in accordance with stated policies and planning, they should apply necessary monitoring and control. In this regard, the most important challenge is a comprehensive and evidence-based identification and analysis, which can consider all functions in relation to the objectives at a general and coherent glance and assess the functions of the health system.
V Yazdi Feyzabadi , Z Khajeh, S Radmerikhi, Mh Mehrolhasani,
Volume 13, Issue 0 (3-2018)
Abstract
One of the main functions of the health systems in each country is health services delivery which includes a wide spectrum of four levels. The first level includes the reduction of disease prevalence, the second level includes early detection, screening and timely treatment. In the third level, we have rehabilitation and relief services, and finally the fourth level is reducing and controlling unnecessary medical interventions. Health services delivery should encompass all of the health needs of each population in the form of these levels. The focus on just one level leads to a reduction in the importance of other levels, and disrupts comprehensive services delivery. It is obvious that, paying attention to the prevention levels can have a significant impact on reducing the later costs and consequences. At present, the provision of services at different levels of Iran's health system is not balanced, and the promotion of these services requires more attention from health policymakers. The health system of Iran is more focused on treatment and medical services and there are many challenges such as poor stewardship and disadvantages of integrated systems in the rehabilitation, relief and palliative services.
S Rezaei, M Soofi, B Karami Matin,
Volume 13, Issue 3 (12-2017)
Abstract
Monireh Rahimkhani, Maryam Gilani,
Volume 20, Issue 1 (6-2024)
Abstract
Antibiotic resistance has increased significantly in recent years. On the other hand, machine learning (ML) algorithms are increasingly used in medical research and healthcare and are gradually improving clinical performance.
Using ML to fight antimicrobial resistance (AMR) is one of the most critical areas of interest among the various applications of these new methods. The rise of antibiotic resistance and managing multidrug-resistant infections that are difficult to treat are important challenges.
Both supervised and unsupervised machine learning tools have been successfully used to predict early antibiotic resistance and thus support clinicians in selecting the appropriate treatment. Machine learning and artificial intelligence (AI) in predicting antimicrobial resistance are among today's sciences. Therefore, an antimicrobial stewardship program (ASP) should be implemented to optimize antibiotic prescribing and limit AMR.
Aliakbar Haghdoost, Samira Emadi, Azam Bazrafshan,
Volume 20, Issue 2 (9-2024)
Abstract
The migration of elites has become a major challenge worldwide. In Iran, in recent years, there has been a remarkable increase in the number of immigrants. Migration often occurs in different ways including educational migration within geographical borders, field migration, experts avoiding professional activities, and forced or semi-forced migration. Due to the fact that each form of migration can lead to diverse problems, it is imperative to pay attention to the nature and complications of each type of migration in the discussion of human resources management.
Manoochehr Karami,
Volume 20, Issue 3 (12-2024)
Abstract
Artificial intelligence (AI) refers to the process in which computers, rather than human intelligence, perform tasks, such as early warning of an epidemic. This editorial aimed to describe the potential applications of digital health and the challenges faced by the health system of Iran concerning the application of artificial intelligence and innovative technology in public health surveillance and early warning of epidemics. The use of new technologies at national and subnational levels for early warning of public health threats requires a suitable platform within the context of disease surveillance systems. The Iran health system currently utilizes a syndromic approach and event-based surveillance to monitor acute respiratory infections. However, the structure of Iran's national communicable disease surveillance system has faced challenges due to the inability to share and exchange data at the level of primary health care data sources. Accordingly, application and integration of AI should be considered as Iran’s health priority to promote infrastructure and technology requirements, including compatibility, interoperability, and strategies for ethical and responsible use by public health authorities. Since pandemics and epidemics have not been limited to the previous ones, such as COVID-19, influenza, SARS, dengue fever, and similar threats, operations planning is required for the integration of artificial intelligence tools to prepare and respond to biological threats promptly by the Iranian Ministry of Health, stakeholders, and other parties.
Saeed Dastgiri, Leyli Mohammad Khanli, Ehsan Farifteh, Elham Davtalab Esmaeili,
Volume 20, Issue 4 (3-2025)
Abstract
Biological evolution leads to changes and extension in biological units’ pool of the population, which is called “gene.” This definition of evolution has comprehensively become more complex today, which includes behavior and cultural units called “meme”, and electronic or digital units called “teme in addition to the biological units. The spread of all three units (gene, meme, and teme) follows a specific evolutionary algorithm inspired by Darwinian principles regarding reproduction and selection of the best adaptation.
The propagation pattern of genes is based on the genetics laws, whereas the epidemiological pattern for meme and teme usually follows viral models. The success of a meme lies in its ability to spread across an entire population like an epidemic to ultimately become a stable and endemic component of that culture.
In conclusion, further research would be essential for the comparison of cultural and behavioral evolutionary algorithms with biological evolution and modeling the development and evolution of meme and teme in order to discover their advantages and disadvantages in human populations.
Rahman Panahi, Armin Baleshzar, Ali Zahmatkesh,
Volume 20, Issue 4 (3-2025)
Abstract
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A review of studies has revealed that the concept of traffic literacy in Iran has not been investigated so far, and there is no valid and reliable tool to measure traffic literacy. In addition, there is a relationship between health literacy in one hand, and managing diseases and accidents, the number of traffic injuries and prevention of road traffic injuries in other hand. Also, considering the relationship between health literacy and the management of diseases and accidents, the rate of traffic injuries, and its role in preventing road traffic injuries, and considering the potential impact of health literacy in promoting safer practices for pedestrians and for having a healthier and safer society, it seems necessary to design a tool to measure traffic literacy in the country. |
Zahra Saboohi,
Volume 21, Issue 1 (6-2025)
Abstract
Electronic health records, as a new tool in monitoring and controlling epidemic diseases in Iranian schools, can help reduce the spread of diseases. This article examines the role of this system in preventing epidemics and increasing coordination between educational and health institutions.
Bahar Haghdoost, Zhaleh Abdi, Iraj Harirchi, Elham Ahmadnezhad,
Volume 21, Issue 2 (9-2025)
Abstract
The COVID-19 pandemic has highly impacted health systems, and the limitations of the national reporting system have reduced the accuracy of estimating the burden of this disease. This study examined the underreporting of COVID-19 cases and hospitalizations using data from the National Survey on Risk Factors for Non-communicable Diseases (STEPS) in Iran in 2021. In this study, 25,425 individuals from the population aged 18 and above were randomly enrolled. In addition to information on non-communicable disease risk factors, participants were questioned about a history of COVID-19 infection, hospitalization, and intensive care unit admission. The frequency of these events was then compared with registry data at the time of data collection. According to the results, 9.3% (95% CI: 8.56 to 9.44) reported a history of COVID-19 infection. Furthermore, among those infected, 12.71% (11.25 to 14.20) reported a history of hospitalization due to COVID-19. Among those hospitalized, 13.74% (8.25 to 18.9) had been hospitalized in intensive care units. Based on this, it is estimated that the sensitivity of recording symptomatic cases was 61.7% (59% to 65%) and for hospitalized cases was 86% (77% to 97.1%).
As a conclusion, it can be stated that the registered incidence of symptomatic COVID-19 cases in Iran was underreported by nearly 40%, and hospitalizations due to COVID-19 were underreported by about 15%. Compared to data from many other countries, including developed nations, this situation can be considered as acceptable.
